{"id":"W2803371826","doi":"10.1149/ma2018-01/6/684","title":"(Invited) Nanoelectronic Lab-on-a-Chip DNA Sensors Based on Nanocarbon Materials","year":2018,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Nanopore and Nanochannel Transport Studies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Nanotechnology; Microfluidics; Biosensor; Carbon nanotube; Materials science; DNA; Lab-on-a-chip; Graphene; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006838395,0.0008847341,0.0003734934,0.0005491174,0.0005250789,0.0009040758,0.0007817466,0.001444133,0.02327955],"category_scores_gemma":[0.000525911,0.0002792386,0.0003845186,0.0002341492,0.0004205141,0.0008298267,0.0005494402,0.001032036,0.01077017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005309236,"about_ca_system_score_gemma":0.0003427557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006698683,"about_ca_topic_score_gemma":0.002492614,"domain_scores_codex":[0.99957,0.00003846921,0.00001270631,0.00009164034,0.0001925064,0.00009458196],"domain_scores_gemma":[0.9996222,0.00005459849,0.00001278657,0.00001299481,0.0002064985,0.00009087386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009495236,0.0002219445,0.0009010131,0.00104778,0.00008074639,0.0007850012,0.0002963631,0.0009000719,0.1624349,0.00640407,0.5778753,0.2481033],"study_design_scores_gemma":[0.00007446338,0.0002975196,0.001486957,0.00006650575,0.00005838865,0.000393643,0.0002077228,0.0015107,0.06161841,0.001495825,0.9327456,0.00004422809],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"editorial","genre_gemma":"methods","genre_scores_codex":[0.09164554,0.1439731,0.08695418,0.05945197,0.3171483,0.001148355,0.001647296,0.003548719,0.2944826],"genre_scores_gemma":[0.09397521,0.02256002,0.01644984,0.007647171,0.030954,0.0003887098,0.0009043705,0.00042895,0.8266917],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02327955,"threshold_uncertainty_score":0.07787782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0104631107683196,"score_gpt":0.2099196423562299,"score_spread":0.1994565315879103,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}